Your browser doesn't support javascript.
loading
pATsi: Paralogs and Singleton Genes from Arabidopsis thaliana.
Ambrosino, Luca; Bostan, Hamed; di Salle, Pasquale; Sangiovanni, Mara; Vigilante, Alessandra; Chiusano, Maria L.
Afiliação
  • Ambrosino L; Department of Agriculture, University of Naples Federico II, Portici, Italy.
  • Bostan H; Department of Agriculture, University of Naples Federico II, Portici, Italy.
  • di Salle P; Department of Agriculture, University of Naples Federico II, Portici, Italy.
  • Sangiovanni M; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.
  • Vigilante A; Department of Genetics, Evolution and Environment, UCL Genetics Institute, University College London, London, UK.; The Francis Crick Institute, Lincoln's Inn Fields Laboratories, London, UK.
  • Chiusano ML; Department of Agriculture, University of Naples Federico II, Portici, Italy.
Evol Bioinform Online ; 12: 1-7, 2016.
Article em En | MEDLINE | ID: mdl-26792975
ABSTRACT
Arabidopsis thaliana is widely accepted as a model species in plant biology. Its genome, due to its small size and diploidy, was the first to be sequenced among plants, making this species also a reference for plant comparative genomics. Nevertheless, the evolutionary mechanisms that shaped the Arabidopsis genome are still controversial. Indeed, duplications, translocations, inversions, and gene loss events that contributed to the current organization are difficult to be traced. A reliable identification of paralogs and single-copy genes is essential to understand these mechanisms. Therefore, we implemented a dedicated pipeline to identify paralog genes and classify single-copy genes into opportune categories. PATsi, a web-accessible database, was organized to allow the straightforward access to the paralogs organized into networks and to the classification of single-copy genes. This permits to efficiently explore the gene collection of Arabidopsis for evolutionary investigations and comparative genomics.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article